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ML-Purdue
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wisebucks.ai
connected to https://github.com/disha101003/wisebucks.ai.git

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StockMetrics.py 6.0 KB
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  1. from time import sleep
    2. 

  2. import requests
    3. 

  3. from bs4 import BeautifulSoup
    4. 

  4. from lxml import etree
    5. 

  5. import numpy as np
    6. 

  6. import pandas as pd
    7. 

  7. 

  8. tickerData = pd.read_csv('Cleaned_Tickers.csv')
    9. 

  9. 

  10. prices = []
    11. 

  11. marketCaps = []
    12. 

  12. PE = []
    13. 

  13. EPS = []
    14. 

  14. ratio = []
    15. 

  15. divY = []
    16. 

  16. Vol = []
    17. 

  17. 

  18. Tickers = tickerData.Tickers
    19. 

  19. Names = tickerData.Names
    20. 

  20. Sectors = tickerData.Sectors
    21. 

  21. 

  22. for i in range(len(tickerData)):  # range(len(tickerData))
    23. 

  23.     ticker = Tickers[i]
    24. 

  24.     URL = f"https://finance.yahoo.com/quote/{ticker}?p={ticker}"
    25. 

  25.     print(i, ticker, URL)
    26. 

  26.     headers = {
    27. 

  27. 

  28.     }
    29. 

  29.     content = requests.request('GET', URL, headers={'path': f'/quote/{ticker}?p={ticker}',
    30. 

  30.                                                     'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 '
    31. 

  31.                                                                   'Safari/537.36',
    32. 

  32.                                                     'scheme': 'https',
    33. 

  33.                                                     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
    34. 

  34.                                                     'Cookie': 'tbla_id=6b642cc0-9ff6-4e67-aa31-1fdeea518b01-tuctae397ee; F=d=cSLEybE9vCX6.RRctEuA7W0H1q8dxhYYra0yu.oc59JM; PH=l=en-US; Y=v=1&n=2jl8gn6380s6n&l=00hj8_l08170l/o&p=f28vvin00000000&iz=400099&r=ee&intl=us; gam_id=y-hOSqWWFG2uJXh4mgLyiH4qY.WFYB27lZfasUHTGUGSecYd_PMQ---A; ucs=tr=1691402027000; OTH=v=2&s=2&d=eyJraWQiOiIwMTY0MGY5MDNhMjRlMWMxZjA5N2ViZGEyZDA5YjE5NmM5ZGUzZWQ5IiwiYWxnIjoiUlMyNTYifQ.eyJjdSI6eyJndWlkIjoiMkZHUVdRQzdISkxYSVVFTzJRTTdBVDZETk0iLCJwZXJzaXN0ZW50Ijp0cnVlLCJzaWQiOiI2WVo4akt0eVpwYTMifX0.8N_R8R5ufYVTxK_9Kwvf7ar27FkH4Vp1hzkrCZhuFVjQrf_0KgfILc3UQvog-kAWpgh1InAMHoH18mGkEpH4yfZTn_nT2s5NrD9hWNScBmtaXuub98ihCYNoVnsV2dULZYFdipXJDQ4aYpwyOeQqhepIJ6it89aRwjkFm1GXr4Q; T=af=QkNBQkJBJnRzPTE2OTI2NDcxMjMmcHM9TmpxeThMOEl3UHNfcUlkajhZMTY5Zy0t&d=bnMBeWFob28BZwEyRkdRV1FDN0hKTFhJVUVPMlFNN0FUNkROTQFhYwFBSU14TGUxSgFhbAFhYXJ0aV92YWliaGF2AXNjAWRlc2t0b3Bfd2ViAWZzAUhwTnlIcXBrbkZoVQF6egFUNzc0a0JBN0UBYQFRQUUBbGF0AVVoRm5rQgFudQEw&kt=EAAFn_5pi5sAS72qhesjXSH3w--~I&ku=FAALxkhH241oqEtbu.3qlAjNPA2U0urNsvmUty1qYD74p24gSlzkcCViMUzBtqWKTC07aYYbk0dEk4YlOvAqljsnSV8wUZUBpEeWo22FSA2_0h26tg_3xiX7EVc6xSqDCT47gekVVMG1HVnHSxhtglnVgXqDP0Me1ziNdCYx2zjDFg-~E; axids=gam=y-hOSqWWFG2uJXh4mgLyiH4qY.WFYB27lZfasUHTGUGSecYd_PMQ---A&dv360=eS1ZVXBPb2NWRTJ1R25kUHozZGtRRzFlNFZZaFB3UFJIblYuNTgwWU85NWo3MFlkbUVnRGw0UEwuSmhKUmwxT0UxQ01KMX5B; maex=%7B%22v2%22%3A%7B%22dadb9128%22%3A%7B%22lst%22%3A1698603940%2C%22ic%22%3A1%7D%7D%7D; GUC=AQEBCAFlQ7FlckIhlgSh&s=AQAAADZJQxbr&g=ZUJl1g; A1=d=AQABBGQS6mMCENyPKExEbHvh2Yj1EBa8aNgFEgEBCAGxQ2VyZVlQb2UB_eMBAAcIZBLqYxa8aNgID8BXLbruyzkQIrPOgM9IKgkBBwoBCw&S=AQAAAkQmK-LnA09xhHuN9Q4E7Qk; A3=d=AQABBGQS6mMCENyPKExEbHvh2Yj1EBa8aNgFEgEBCAGxQ2VyZVlQb2UB_eMBAAcIZBLqYxa8aNgID8BXLbruyzkQIrPOgM9IKgkBBwoBCw&S=AQAAAkQmK-LnA09xhHuN9Q4E7Qk; A1S=d=AQABBGQS6mMCENyPKExEbHvh2Yj1EBa8aNgFEgEBCAGxQ2VyZVlQb2UB_eMBAAcIZBLqYxa8aNgID8BXLbruyzkQIrPOgM9IKgkBBwoBCw&S=AQAAAkQmK-LnA09xhHuN9Q4E7Qk; gpp=DBAA; gpp_sid=-1; cmp=t=1700420968&j=0&u=1YNN; PRF=t%3DAAPL%252BWEC%252B%255EGSPC%26newChartbetateaser%3D1; __gpi=UID=00000cdb8650fcba:T=1700420969:RT=1700422041:S=ALNI_MZcG6j_95mgHOGFvLKM1tyq3m6zvA; __gads=ID=281786745495dc8c:T=1700422045:RT=1700422045:S=ALNI_MY19a0zNj7xmJIluuK4Ocoiz8Fwtg'
    35. 

  35. 

  36.                                                     })
    37. 

  37.     sleep(5)
    38. 

  38.     soup = BeautifulSoup(content.text, 'html.parser')
    39. 

  39.     dom = etree.HTML(str(soup))
    40. 

  40.     # print(soup.text)
    41. 

  41.     try:
    42. 

  42.         price = dom.xpath(
    43. 

  43.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[1]/table/tbody/tr[1]/td[2]')[
    44. 

  44.             0].text
    45. 

  45.         mcap = dom.xpath(
    46. 

  46.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[2]/table/tbody/tr[1]/td[2]')[
    47. 

  47.             0].text
    48. 

  48.         pe = dom.xpath(
    49. 

  49.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[2]/table/tbody/tr[3]/td[2]')[
    50. 

  50.             0].text
    51. 

  51.         eps = dom.xpath(
    52. 

  52.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[2]/table/tbody/tr[4]/td[2]')[
    53. 

  53.             0].text
    54. 

  54.         divYd = dom.xpath(
    55. 

  55.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[2]/table/tbody/tr[6]/td[2]')[
    56. 

  56.             0].text
    57. 

  57.         vol = dom.xpath(
    58. 

  58.             '/html/body/div[1]/div/div/div[1]/div/div[3]/div[1]/div/div[1]/div/div/div/div[2]/div[1]/table/tbody/tr[8]/td[2]')[
    59. 

  59.             0].text
    60. 

  60.         print(price, mcap, pe, eps, divYd, vol)
    61. 

  61.         if price != 'N/A':
    62. 

  62.             prices.append(float(str(price).replace(",", "")))
    63. 

  63.             marketCaps.append(mcap)
    64. 

  64.             EPS.append(float(str(eps).replace(",", "")))
    65. 

  65.             if pe != 'N/A':
    66. 

  66.                 PE.append(float(str(pe).replace(",", "")))
    67. 

  67.                 ratio.append(round(float(str(eps).replace(",", ""))/float(str(pe).replace(",", "")), 3))
    68. 

  68.             else:
    69. 

  69.                 PE.append(-1)
    70. 

  70.                 ratio.append(-1)
    71. 

  71.             if 'N/A' in divYd:
    72. 

  72.                 divY.append(-1)
    73. 

  73.             else:
    74. 

  74.                 div = float(str(divYd).split(sep='(')[1].split(sep='%')[0])
    75. 

  75.                 divY.append(div)
    76. 

  76.             Vol.append(float(str(vol).replace(",", "")))
    77. 

  77. 

  78.         else:
    79. 

  79.             print("WAH")
    80. 

  80.             raise Exception
    81. 

  81.     except:
    82. 

  82.         print(prices, marketCaps, PE, EPS, divY, Vol)
    83. 

  83.         print("Fail")
    84. 

  84.         prices.append(-1)
    85. 

  85.         marketCaps.append(-1)
    86. 

  86.         PE.append(-1)
    87. 

  87.         EPS.append(-1)
    88. 

  88.         ratio.append(-1)
    89. 

  89.         divY.append(-1)
    90. 

  90.         Vol.append(-1)
    91. 

  91.     sleep(3)
    92. 

  92. 

  93. print(prices)
    94. 

  94. print(marketCaps)
    95. 

  95. print(PE)
    96. 

  96. print(EPS)
    97. 

  97. print(ratio)
    98. 

  98. print(divY)
    99. 

  99. print(Vol)
    100. 

  100. d = {'Ticker': Tickers,
    101. 

  101.      'Price': prices,
    102. 

  102.      'MCap': marketCaps,
    103. 

  103.      'PE': PE,
    104. 

  104.      'EPS': EPS,
    105. 

  105.      'Earnings_Yield': ratio,
    106. 

  106.      'Div_Yield': divY,
    107. 

  107.      'Volume': Vol}
    108. 

  108. df = pd.DataFrame(data=d)
    109. 

  109. df.to_csv('final1.csv')
    110.
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